scholarly journals A Procedure for the Selection of Single Sampling Plans by Variables Based on Pareto Distribution

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Geetha Sathya Narayanan ◽  
Vijayaraghavan Rajarathinam
Keyword(s):  
Pareto Distribution ◽  
Quality Characteristic ◽  
Statistical Quality Control ◽  
Implicit Assumption ◽  
Sampling Plans ◽  
Nonnormal Distributions ◽  
Sampling Inspection ◽  
Continuous Scale ◽  
Selection Of ◽  
Product Control

Product control in statistical quality control is the methodology that deals with procedures for taking decisions about one or more lots of finished products manufactured by production processes. Sampling inspection by variables is one of the major classifications of product control and comprises procedures for deciding about the disposition of a lot of individual units based on sample measurements of units on a quality characteristic under study. These procedures are defined under the assumption that the quality characteristic is measurable on a continuous scale, and the functional form of the probability distribution must be known. Inspection procedures which have been developed under the implicit assumption that the quality characteristic is distributed as normal with the related properties are found in the literature of product control. The assumption of normality may not be realized often in practice, and it becomes indispensable to investigate the properties of sampling plans based on nonnormal distributions. In this paper, a single sampling plan by variables is formulated and evaluated when the quality characteristic is assumed to be distributed according to a Pareto distribution. A procedure is developed for determining the parameters of the plan for specified requirements to ensure protection to both the producer and consumer.

Comparison of insulin sensitivity indices properties calculated from OGTT

Open Medicine ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. 567-574 ◽  
Author(s):  
Jana Chrenova ◽  
Zuzana Rausova ◽  
Adela Penesova ◽  
Ladislav Dedik
Keyword(s):  
Insulin Sensitivity ◽  
Glucose Tolerance Test ◽  
Statistical Significance ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Oral Glucose Tolerance ◽  
Individual Subject ◽  
Sensitivity Indices ◽  
Continuous Scale ◽  
Selection Of

AbstractThe aim of this study was to present the properties of insulin sensitivity indices formulas to justify selection of formulas to evaluate of insulin sensitivity for calculation from an oral glucose tolerance test (OGTT) data. Twelve of the most applicable formulae for ISI calculation were analyzed in the view of two sets of results: 1) point contrasts, calculated as the ratio of average ISI values in lean and obese groups of patients; and 2) interval contrasts, calculated as ratios of T from the two-sided t-test, evaluated as dimensionless, mutually comparable contrasts within a continuous scale. Statistical significance of individual ISIs in terms of their contrasts was evaluated by two-sided t-tests. P<0.001 was a considered statistically significance between a group of 59 healthy volunteers with BMI<25 kg/m2 and a group of 63 volunteers with BMI≥25 kg/m2 who underwent frequent OGTT sampling. To compare data of an individual subject with the standard, we recommend selecting the formulas with a high point contrast. To compare of data of several subject groups, we recommend using the formulas with a high interval contrast.

Optimal designing of SkSP-2 skip-lot sampling plan for normally distributed quality characteristics

2017 ◽  
Vol 40 (7) ◽  
pp. 2240-2248 ◽  
Author(s):  
Saminathan Balamurali ◽  
Jambulingam Subramani
Keyword(s):  
Sampling Plan ◽  
Quality Characteristic ◽  
Optimal Parameters ◽  
Optimal Plan ◽  
Sample Number ◽  
Sampling Plans ◽  
Sampling Schemes ◽  
The Cost ◽  
Optimal Designing ◽  
Average Sample

Skip-lot sampling plans have been widely used in industries to reduce the inspection efforts on products that have an excellent quality history. These skip-lot sampling schemes are economically advantageous and useful to minimize the cost of the inspection of the final lots. Also, the skip-lot concept is sound and useful in the design of sampling plans. In this paper, we propose a designing methodology to determine the optimal parameters of a skip-lot sampling plan of type SkSP-2 when the quality characteristic under study follows a normal distribution. The optimal plan parameters are determined to minimize the average sample number subject to satisfying the producer’s and consumer’s risks simultaneously at the acceptable and limiting quality levels, respectively. An optimization problem is formulated in order to construct tables for determining the optimal parameters of the proposed sampling plan for both known and unknown standard deviation cases and the results are compared with the variables single sampling plans.

Bayesian Reliability Sampling Plans under the Conditions of Rayleigh-Inverse-Rayleigh Distribution

2014 ◽  
Vol 0 (0) ◽  
Author(s):  
S. Kalaiselvi ◽  
A. Loganathan ◽  
R. Vijayaraghavan
Keyword(s):  
Probability Distributions ◽  
Rayleigh Distribution ◽  
Predictive Distribution ◽  
Life Testing ◽  
Sampling Plans ◽  
Sampling Inspection ◽  
Single Sampling Plan ◽  
Reliability Sampling Plans ◽  
Quality Of Products

AbstractReliability sampling plans are used to take decisions on the disposition of lots based on life testing of products. Such plans are developed taking into the consideration of relevant probability distributions of the lifetimes of the products under testing. When the quality of products varies over lots, then a predictive distribution of the lifetime should be used to design sampling plans. In this paper, designing of reliability single sampling plan based on the predictive distribution of the lifetime is considered. It is assumed that sampling inspection is carried out through life testing of products with hybrid censoring. The predictive distribution is obtained assuming that the probability distribution of the lifetime of the product is Rayleigh and the process parameter has an inverse-Rayleigh prior. Plan parameters are determined using hypergeometric, binomial and Poisson probabilities, providing protection to both producer as well as consumer.

Selection of tightened two-level continuous sampling plans

1993 ◽  
Vol 20 (2) ◽  
pp. 271-284 ◽  
Author(s):  
C. Kandasamy ◽  
K. Govindaraju
Keyword(s):  
Sampling Plans ◽  
Continuous Sampling ◽  
Selection Of
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